Ensuring Robust Flood Risk Management in Ho Chi Minh City

Ho Chi Minh City faces significant and growing flood risk. Recent risk reduction efforts may be insufficient as climate and socio-economic conditions diverge from projections made when those efforts were initially planned. This study demonstrates h...

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Bibliographic Details
Main Authors: Lempert, Robert, Kalra, Nidhi, Peyraud, Suzanne, Mao, Zhimin, Tan, Sinh Bach, Cira, Dean, Lotsch, Alexander
Language:English
en_US
Published: World Bank, Washington, DC 2013
Subjects:
Online Access:http://documents.worldbank.org/curated/en/2013/05/17784406/ensuring-robust-flood-risk-management-ho-chi-minh-city
http://hdl.handle.net/10986/15603
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Summary:Ho Chi Minh City faces significant and growing flood risk. Recent risk reduction efforts may be insufficient as climate and socio-economic conditions diverge from projections made when those efforts were initially planned. This study demonstrates how robust decision making can help Ho Chi Minh City develop integrated flood risk management strategies in the face of such deep uncertainty. Robust decision making is an iterative, quantitative, decision support methodology designed to help policy makers identify strategies that are robust, that is, satisfying decision makers' objectives in many plausible futures, rather than being optimal in any single estimate of the future. This project used robust decision making to analyze flood risk management in Ho Chi Minh City's Nhieu Loc-Thi Nghe canal catchment area. It found that the soon-to-be-completed infrastructure may reduce risk in best estimates of future conditions, but it may not keep risk low in many other plausible futures. Thus, the infrastructure may not be sufficiently robust. The analysis further suggests that adaptation and retreat measures, particularly when used adaptively, can play an important role in reducing this risk. The study examines the conditions under which robust decision making concepts and full robust decision making analyses may prove useful in developing countries. It finds that planning efforts in developing countries should at minimum use models and data to evaluate their decisions under a wide range of conditions. Full robust decision making analyses can also augment existing planning efforts in numerous ways.